1. News Channels a Substitute/Compliment for Newspapers Essay Example

market has attracted interest from international media giants as they vie for a share of it. The sector has also received foreign direct investment (FDI) totaling US$ 88 million. Furthermore, the government approved a total of 13 FDI proposals in 2006.

The media and entertainment industry in India is experiencing significant growth due to factors such as the corporatization of the film industry, a thriving television sector, a rapidly expanding radio sector, a growing market for print products, and technological advancements. India is embracing these global changes and is poised to grow alongside the industry.

The growth rates of different sectors within the Media and Entertainment Industry are as follows:

The increase in cable network usage and the rise of business channels raises questions about their impact on traditional newspaper usage.

The television industry in India is currently thriving.

It has over 350 channels and is now ranked third globally in terms of television market size.

The television market in India is nearly equivalent to the entire US market, reaching around 119 million households, accounting for roughly 60 percent of all households in the country. Among these households, approximately 50 million have access to cable television services. With low penetration levels, there is significant potential for growth in this industry. According to PwC, the Indian television market generated revenues of US$3.4 billion in 2005.

The business news industry is forecasted to experience a 22 percent Compound Annual Growth Rate (CAGR), reaching

US$ 11.5 billion by 2011, driven by the introduction of numerous channels. Business news channels offer several advantages: they can rapidly reach a wide national or regional audience, target local viewers through independent stations and cable, utilize visual and auditory elements to convey messages effectively as television is a medium that builds images and relies on visuals, and provide the ability to simultaneously compare different perspectives on an issue by scanning multiple news channels. Furthermore, television offers a greater abundance of news content. Nonetheless, drawbacks include high costs for creative production and airtime, potential annoyance from repeated telecasts of the same news stories, decreased audience selectivity, and the inability to reference past news broadcasts. Print media, particularly newspapers, are anticipated to grow annually at a rate of 12% due to increased literacy rates in India and higher readership figures for newspapers and magazines. With 78 papers being published daily or weekly in India alone, it possesses the world's second-largest newspaper market after China.

The newspaper market in India is experiencing rapid growth due to the expanding middle class and decreasing illiteracy rates (estimated at 35%). With daily sales of 7 million copies, print newspapers are taking advantage of the relatively low Internet penetration. Additionally, they represent upward social mobility and cultural prestige for Indians.

India still has approximately 350 million literate individuals who choose not to purchase newspapers. While publishers celebrate their growing circulation numbers, many editors are searching for more qualified and experienced journalists. The advantages of newspapers include the ability to reach a large number of people within a specific geographic area, comprehensive local market coverage, unlimited exposure to content, and the tactile enjoyment of

physical copies. However, there are also disadvantages such as limitations in photo reproduction impacting creativity, the price-oriented nature of newspapers, their short shelf life as they are typically read once and discarded, time-consuming reading process, and their relatively unattractive appearance. In India, major newspaper companies like Bennett, Coleman ; Co. Ltd. (Times Group), Hindustan Times, Indian Express, Malayala Manorama, and Dainik Bhaskar have expanded their coverage areas, introduced new sections, and formed collaborations with news channels."So, the question arises: What will be the impact of Business news channels on newspapers in the future? Will news availability on Cable networks pose a major challenge to the printed newspapers? Should newspaper companies concentrate on the print media and restrain or grab the new opportunity in the cable network world? Do people who have cable connections listen to news on business news channels? If yes, how regularly do they listen to news on business news channels? Is listening to news on business news channels complimentary to newspaper or a substitute? Additionally, the study also looked into some associated queries such as, for which type of news, the newspaper is preferred more, and what factors favor the reading of the newspaper.

Methodology: In order to carry out this study, a structured questionnaire was designed."

Empirical data was collected through the use of a questionnaire to gather information on readers' attitudes towards television usage and the amount of time they spent watching TV. The survey method was employed to collect data from individuals who had access to cable networks and were considered moderate or heavy television users. The questionnaires were distributed in offices and markets located in Faridabad. To prevent any

influence from interviewers, the survey was self-administered. A total of 120 respondents took part in the survey, but due to incomplete data, steps were taken to minimize common method variance by ensuring anonymity and stressing the importance of providing honest answers. Data collection involved multiple choice questions and Likert scale questions. The collected data underwent descriptive statistical analysis as well as frequency analysis.

The data was cross-tabulated to test various hypotheses of independence, primarily using the chi-square test. Reliability analysis was performed on scaled data to check for consistency before further analysis. Factor analysis was conducted to identify the factors necessary to explain the relationship patterns among the variables being studied. Additionally, factor analysis was used to assess how well the hypothesized factors explained the observed data and the unique variance observed in each variable.

Results and Discussion:

This section presents the results of the data analysis and provides discussion on them.

The analysis begins by examining the demographic characteristics of the respondents and their news consumption patterns on various news channels, including the number of years they have been accessing these channels and how frequently they do so. The demographics of the participants were collected under three categories: age, educational background, and profession. Upon analyzing these factors, it was found that 43.14% of the participants belonged to the 18-24 age group, whereas 23.53% fell into the 25-31 age group.

The group's age distribution was as follows: 69% were aged between 32 and 38, 9.8% were aged between 39 and 44, and 7.84% were above the age of 45. Among them, 58.2% were working executives while students accounted for 41.18%.

17.65% of respondents had studied engineering, 36.27% had

a background in management, 11.76% came from arts, and the remaining 34% had different educational backgrounds.

The "Other" category experienced a 31% decrease. This category encompasses factors like frequency of television access, duration of access, types of news items watched on News channels, and reasons for selecting newspaper or news channels for news media.

Frequency Analysis

Percentage of people watching television for news

Yes: 93 (91.17%)
No: 9 (8.82%)
Respondents' behavior involves the use of television to listen to news and related factors such as frequency and duration of usage.

The main goal is to determine the number of individuals from the chosen population who have cable connections and watch television news. The presented frequency distribution displays that 91.17% of the participants watch news on TV, while the remaining 8.82% do not. Analysis indicates that over 90% of respondents watch news daily or every 2-3 days, and more than 41% spend over 60 minutes watching news channels. The frequency distribution also shows the respondents' time spent on television: between 30 minutes and 1 hour, 59 individuals (57%).

84% (1 to 3 Hours) : 34 (33.33%) ; 3 hours : 9 (8.82%) Total : 102

It is also evident from the data that people prefer both watching news on news channels as well as reading news from newspapers. However, the percentage of watching news on news channels is almost equal to reading newspapers.

Frequency distribution of the respondents as per their frequency of reading newspapers and watching news on news channels:

Frequency (Percentage) News on News Channels Reading Newspaper Daily :

75 (73.53%) Reading Newspaper : 70 (68%)

63% Once in 2-3 days 18 (17.65%)19 (18. 63%) Once in a week 4 (3. 92%)8 (7. 84%) Once in 15 days1 (0.

98%)1 (0.98%) Never 4 (3. 92%)4 (3. 92%) Total =102Frequency distribution of respondents based on time spent reading newspapers and news on the Internet. Percentage of respondents' time spent watching news on news channels and reading newspapers:

• 5-10 minutes: 21 (20. 58%)16 (15.68%0)
• 10-30 minutes: 45 (44. %)

11% took 30-60 minutes, 23% took over 60 minutes, and 4% did not take any time.

96%) Total 102

Frequency analysis of reading newspaper vs.

listening News on News Channels This section focuses on testing two null hypotheses related to the frequency and time spent on reading newspapers and listening to news on news channels. The first null hypothesis compares the frequency of usage between newspapers and news channels. The test utilized individual respondent's scores, with the null hypothesis stating that people who use both methods listen to news on news channels as frequently as they read newspapers (µ1=µ2). On the other hand, the alternative hypothesis suggests that people who use both methods listen to news on news channels less frequently than they read newspapers (µ1? µ2). By conducting a two-tail z-test at a significance level of 5 percent, we accept the null hypothesis, concluding that respondents listen to news on news channels as frequently as they read newspapers. The second null hypothesis examines the time spent on reading newspapers versus listening to news on news channels.

The text examines a hypothesis test about the time spent by respondents who read news using both newspapers

and news channels. The null hypothesis states that individuals who use both media spend an equal amount of time listening to news channels as they do reading newspapers, while the alternative hypothesis suggests they spend less time on news channels. Using a two-tail z-test at a 5 percent significance level, the null hypothesis is accepted. This implies that people who use both media spend an equivalent amount of time listening to news on news channels as reading newspapers. Furthermore, the section explores the relationship between listening to news on news channels and various respondent characteristics including years of cable network usage, television viewing time, age group, educational background, and profession.

Null Hypothesis

H0: There is no correlation between the respondent's years of accessing the Cable network and their engagement with news on news channels.

The null hypotheses are as follows: H0: There is no association between time spent on watching television and listening to news channels, H0: There is no association between the age of the respondents and news listening on news channels, H0: There is no association between the profession of the respondents and listening to news on news channels, and H0: There is no association between educational background and listening to news on news channels.

According to the data, individuals who have had a cable connection for more than six years are more likely to regularly listen to news on news channels. Around 70.5% of those with over 6 years of cable network experience have a higher percentage of daily news listening compared to those with less than 6 years of cable network experience.

The table below displays the number of respondents who listen to news on news channels based on their frequency and years of using cable connection. The categories include those who use cable connection daily, once in 2-3 days, once a week, once in 15 days, and never. The total number of respondents is given for each category of years using cable connection, which include less than 3 years, 3-6 years, and more than 6 years. The data presented in this table is used to test null hypotheses.

Table 5: Years of accessing Cable Connection vs. Watching news on News Channels
Frequency of respondents who listening news on News Channels
Years Using Cable Connection
Daily
Once in 2-3 days
Once a week
Once in 15 days
Never
Total
<3yr
122
20
218
3-6 yr
102
0
12
>6yr
48
156
1272

Total: 1027
01
98
14
102

The table below compares the frequency of respondents listening to news on news channels with their television usage duration. The categories include daily, once in 2-3 days, once a week, once in 15 days, and never. The duration of television usage is broken down into three categories: 30 min - 1 hr, 1-3 hrs, and greater than 3 hrs. The total number of respondents is given for each combination of frequency and duration.

Frequency of respondents listening news on News Channels
Television Usage Duration
Daily
Once in 2-3 days
Once a week
Once in 15 days
Never Total
30 min – 1 hr
401
140
459

1-3 hrs
256
300
34

>3 hrs
52
11
9

Total
1027
01
98
14
102

The calculated chi-square value for this data is 13.5, which is compared to the

tabulated value of 15.

At a 5 percent significance level and with 8 degrees of freedom, the null hypothesis is accepted. This suggests that there is an association between the amount of time spent watching television and listening to news on the internet. The data presented shows the frequency of respondents watching news on a specific News Channel, categorized by age groups. The total number of respondents in each age group is also provided. This information is used to test null hypothesis 3.

The chi-square value obtained is 16.00, while the tabulated value at a 5 percent level of significance and 16 degrees of freedom is 26.29. Based on these findings, there is no evidence to reject the null hypothesis.

There is no connection between the age of the respondents and their habit of reading news on the internet. The frequency of respondents watching news on news channels is divided by their professional background. The options for frequency are daily, once in 2-3 days, once a weekend, once in 15 days, and never. The total number of working respondents is 42, student respondents is 28, and the overall total is 70. The null hypothesis 4 is being tested using this dataset. The chi-square value calculated is 2.25 out of 9.48, with a significance level of 5 percent and 4 degrees of freedom.

It is concluded that there is no evidence against the null hypothesis in this case. It means that there is no association between the profession of the respondents and watching the news on news channels.

Educational background vs. Watching news on News Channels

Frequency of respondents who listen to news on News Channels:

Educational Background: Daily | Once in 2-3

days | Once a week | Once in 15 days | Never | Total

Engineer: 10,600 | 2,180 | -

Management: 3,025 | 0 | 0 | 37

Arts: 840 | 0 | 0 | - | 12

Others: 2273 | - | - | - | 12 | 35

Total: 70,198 | 14,102 | - | - | -

Total = 18.84,21.02,12

The data is analyzed for testing null hypothesis 5. The calculated chi-square value is 18.

Comparing 84 to 21.2 at a 5% level of significance and with 12 degrees of freedom, it can be concluded that there is no evidence to reject the null hypothesis. Therefore, there is no association between educational background and listening to news on news channels. In summary, based on the tests conducted on the five hypotheses discussed above, it can be inferred that watching news on news channels is not related to time spent on television, years of using a cable connection, age, profession, or educational background of the respondents.

The primary goal is to analyze the factors that contribute to the preference of watching news on news channels or reading newspapers, with a specific focus on determining the major factors for selecting the Internet or newspapers as sources of news. Factor analysis is utilized for this purpose. For the Internet, data is collected on seven factors: convenience, presentation, cost advantage, more updated news, multiple reporting, more news, and availability. Likert scale is employed in collecting this data. In a similar manner, data on four factors - habit, convenience, handy, and local news - is collected for reading newspapers. The ratings of attributes for newspaper readers and news channel listeners are as follows.
Attributes

Rating Scores
Listeners of news on television Convenience: 3.88 + 0.

19 (4. 07) presentation 3. 85 + 0.17 (4. 03) more Updated 4.

The amount of news reported is 3.96 + 0.18 (4.14) multiple times, with 0.06 + 0.19 (4.26) as the reporting factor.

37 + 0.23 (3.61) Readers of Newspapers Habit 3.91 + 0.18 (4.

31) Convenience4. 16 + 0.15 (4.32) Handy 3.91 + 0.19 (4.

10) Local News 3. 93 + 0.20 (4.14) Availability4.18 + 0.15 (4.34) Calculations are made to determine the mean scores, standard error, and mode values (in brackets) for television news listeners and newspaper readers in order to rank attributes. The highest mean scores are found for more updated news, followed by multiple reporting, convenience, and presentation.

The minimum mean score is for the amount of news attribute. For newspaper readers, the highest mean score is for availability, followed by convenience, habit, local news, and handy. The reliability test Table 11 presents the reliability coefficient, KMO, and Bartlett test output. For listeners of news on News Channels, the reliability coefficient is 0.766 (calculated for 10 attributes together) and KMO is 0.772. The Bartlett Test resulted in a Chi-square value of 97.

717 Df =10 Significance=0.00 Readers of Newspapers 0.60 Chi-square=104.941 Df =10 Significance=0.

00 Factor Analysis The data also undergoes a reliability test and factor analysis. The reliability coefficient (Cronbach’sAlpha) has a value of approximately 0.766, which is considered an acceptable measure of data reliability. The value of Cronbach's alpha was computed for all ten attributes.

Regarding listeners of news on news channels, the following attributes have been analyzed. The Kaiser-Mayor-Olkin (KMO) values indicate

that the measure of sampling adequacy is 0.772, suggesting that factor analysis is appropriate. Additionally, Bartlett’s test of sphericity yielded a chi-square value of 97.17 at 10 degrees of freedom and a significance value of 0.00. These Bartlett’s test values imply that the sample inter-correlation matrix originated from a population in which the inter-correlation matrix is an identity matrix. This means that each variable has a perfect correlation with itself (r=1) but does not correlate with other factors. Based on factor analysis, only one factor/component emerged to account for 48.826 percent of the variation. This factor/component highlights the highest amount of shared variance, also referred to as communality, particularly in terms of convenience.

The factor loading shows a high correlation between convenience and being more updated for news listeners on news channels. This correlation is found in factor 1, also known as the perfection dimension. The component matrix for watching news on news channels reveals the following loadings:

Convenience: 778.605

Presentation: 707.500

More updated: 744.554

Multiple reporting: 645

416 amount of news variation can be explained by 605 48.826 and .366 table 13's component matrix(a) component communality factor.
Factor 1 is related to habit and has a value of .626.
Factor 2 is related to convenience and has a value of .721.
Factor 3 is related to handy.

696. 484 Local news. 754.568 Availability Variance explained. 697 49. 007.

The values of Kaiser-Mayor-Olkin (KMO), the measure of sampling adequacy, for the five attributes towards readers of newspapers is 0.760. This indicates that factor analysis is appropriate. The chi-square value of Bartlett’s test of sphericity is 104.941 at 10 degrees of freedom and a significance value of 0.00. Based on Bartlett's test, the sample inter-correlation matrix

came from a population with an identity matrix as the inter-correlation matrix. After conducting factor analysis, one factor/component emerged that explains 49 percent of the variance.

The common factor explains the highest proportion of variance for local news and its correlation with convenience of newspaper readers. The distribution of respondents' preferences for different types of news in various media is shown in the table below.

53% (26) (25. 5%) Sports News 19 (18. 6%) (33) (32. 4%) (37) (36.3%) (13) (12. 7%) International News 20(19. 6%) (29)(28.

4%)44(43. 1%)9(8. 8%) Bollywood/ Entertainment News15(14.7%)36(35. 3%)33(32.

4%)18(17. 6%)

Editorial & analysis

49(48. 0%)18(17. 6%)21(20.6%)14(13. 7%) Categories of News This section shows the respondents' preferences for television and newspaper when it comes to different types of news, such as sports and business. It can be concluded that both mediums are favored for general news, with news channels being preferred for business and stock news, and newspapers serving as an important source for editorials. Overall, people read newspapers and watch news channels for all categories of news.

Conclusion: Based on the data analysis, it is concluded that 91.17%

of people who have cable network access and access television daily watch the news on news channels. The majority of these viewers are quite regular, with 73.53% watching the news on news channels daily. Additionally, 17.5% of people read news on the Internet within 2-3 days. Among those who read news on the Internet daily, it was observed that 64% spend less than 30 minutes watching news on news channels. People who use both newspapers and news channels for news display equal frequency in using both mediums. There is no association found between time spent on television, number of years using a cable connection, age, and watching the news on news channels. Similarly, no association was found between profession and educational background and watching the news on news channels. Furthermore, the usage of the Internet varies across different categories of news.

Among the various news categories, Bollywood news is most popular on news channels, followed by business and stock news. Factor analysis has revealed that the primary factor for newspaper usage is local news coverage, while for news channels, convenience is the dominant factor. Therefore, it can be concluded that reading news online complements rather than substitutes for reading newspapers. Few individuals rely solely on either newspapers or news channels for their news consumption, indicating no imminent threat to newspapers. Cable connection duration and television viewing time positively correlate with newspaper usage, suggesting newspapers remain a popular medium for accessing news. Reading habits are not influenced by factors such as age, educational background, or profession.

When it comes to Bollywood news, business/stock news, and international news, news channels are highly popular.